2024 : 11 : 21
فارسی
Ali Valinejad
Academic rank:
Assistant Professor
ORCID:
Education:
PhD.
ScopusId:
HIndex:
Faculty:
Faculty of Mathematical Sciences
Address:
Phone:
01135302478
E-mail:
valinejad [at] umz.ac.ir
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Education
Courses
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Education
PhD. in
(2007 - 2012)
Thesis title:
MSc. in Applied Mathematic , Tarbiat Modares University of Tehran , Iran
(2000 - 2003)
Thesis title:
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Courses
Bachelor Of Science
Numerical Linear Algebra
Data Structures and Algorithms
Master Of Science
Machine Learning(En)
Machine Learning(Fa)
Research activities
Journal Papers
THE EFFECT OF SINGULARITY ON A TYPE OF SUPPLEMENTED MODULES
Ali Reza Moniri Hamzekolaee, Ali Valinejad (2023)
A numerical technique for solving nonlinear fractional stochastic integro-differential equations with n-dimensional Wiener process
Elnaz Aryani, Afshin Babaei, Ali Valinejad (2022)
An accurate approach based on modified hat functions for solving a system of fractional stochastic integro-differential equations
Elnaz Aryani, Afshin Babaei, Ali Valinejad (2021)
Numerical solution of regularised long ocean waves usingperiodised scaling functions
Mostafa BAKHODAY-PASKYABI, Ali Valinejad, Haman DEILAMI AZODI (2019)
A Recursive Solution Approach to Linear Systems with Non-Zero Minors
Ahmad Moradi, Atena Kameli, Hossein Jafari, Ali Valinejad (2019)
Conference Papers
An adaptive time-stepping algorithm for a stochastic Lotka–Volterra competitive model with time-dependent delays
Ali Valinejad, Zahra Zarei Valojaei, Afshin Babaei (2023)
Theses
LSTM Neural Networks for Disease Prediction
Ali Kadhim Msawil, Rohollah Yousefpour, Ali Valinejad (2022)
Image Segmentation of Medical Images using Contrastive Learning
Hussein Khalid Alyaseri Azeez, Reza Nadimi, Ali Valinejad (2022)
یادگیری نیمه نظارتی برای بخش بندی تصاویر پزشکی
Hamzah Shaalan Nafnaf Alyasari, Ahmad Moradi, Ali Valinejad (2022)
تشخیص ناهنجاری در داده های مراقبت های بهداشتی با استفاده از یادگیری بدون نظارت
Ahmad Waad Abd Ali, Reza Nadimi, Ali Valinejad (2022)
Students
Name:
Ahmed Waad Abd Ali
AcademicLevel:
Master
Field:
Computer sciences
Thesis:
Anomaly detection in healthcare data using unsupervised learning
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